scholarly journals An ASP-based Solution to the Chemotherapy Treatment Scheduling problem

2021 ◽  
pp. 1-17
Author(s):  
CARMINE DODARO ◽  
GIUSEPPE GALATÁ ◽  
ANDREA GRIONI ◽  
MARCO MARATEA ◽  
MARCO MOCHI ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Treatment Time ◽  
Answer Set Programming ◽  
Real Data ◽  
Complex Problem ◽  
Scheduling Problem ◽  
Constant Number ◽  
Chemotherapy Treatment ◽  
Number Of Patients ◽  
Treatment Plans

Abstract The problem of scheduling chemotherapy treatments in oncology clinics is a complex problem, given that the solution has to satisfy (as much as possible) several requirements such as the cyclic nature of chemotherapy treatment plans, maintaining a constant number of patients, and the availability of resources, for example, treatment time, nurses, and drugs. At the same time, realizing a satisfying schedule is of upmost importance for obtaining the best health outcomes. In this paper we first consider a specific instance of the problem which is employed in the San Martino Hospital in Genova, Italy, and present a solution to the problem based on Answer Set Programming (ASP). Then, we enrich the problem and the related ASP encoding considering further features often employed in other hospitals, desirable also in S. Martino, and/or considered in related papers. Results of an experimental analysis, conducted on the real data provided by the San Martino Hospital, show that ASP is an effective solving methodology also for this important scheduling problem.

scholarly journals SAT0476 COMPLIANCE AND PERSISTENCE OF ANTI-OSTEOPOROTIC TREATMENTS IN PATIENTS WITH HIP FRACTURE

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1194.2-1195
Author(s):  
S. Paredes ◽  
M. Guinovart ◽  
A. Basco ◽  
C. Llop
Keyword(s):  
Hip Fracture ◽  
Health Service ◽  
Hospital Discharge ◽  
Treatment Time ◽  
Osteoporotic Fractures ◽  
Main Diagnosis ◽  
Pharmacological Treatments ◽  
Cross Sectional ◽  
Good Compliance ◽  
Number Of Patients

Background:Osteoporotic fractures have a high health and economic impact. The best strategy to minimize the incidence of fractures is, certainly, the prevention of these that includes pharmacological treatments. However, long-term discontinuation treatment and sub-optimal compliance of the treatment are common.Objectives:The aim of the study is to quantify the therapeutic compliance and permanence of the osteoporosis pharmacological treatments for patients who were discharged from hospitals in Catalonia with hip fracture during 2017.Methods:From the Hospital Discharge Database of the Catalan Health Service, all patients who had been discharged during 2017 were selected with the main diagnosis of femur fracture, according to the coding CIM-9. The consumption of drugs to assess compliance and permanence was obtained from the Catalan Health Service pharmacy Database. The study period was 18 months from the date of hospital discharge. Patients who died, moved to other areas or switched their treatment were excluded from the study. Good compliance was considered when sufficient drug was obtained to cover 80% of the time since treatment was prescribed until the end of the study period. In the case of denosumab, good post-fracture compliance was considered when the treatment time was remained at least 12 months. Permanence was considered positive if a drug had been obtained during the last three months of the study period. To compare the differences in compliance and permanence between the patients treated with different drugs, the chi-square statistic was used, considering statistically significant differences if p<0.05.Results:8,354 patients were discharged with the main diagnosis of hip fracture. Of these, 1,712 patients (20.49%) were treated after been discharged. After applying the exclusion criteria, the final sample was made up of 1,327 patients. 81,54% were women, and the median age was 84,79 years.The most commonly used treatments were bisphosphonates (69%), denosumab (23%) and teriparatide (7%)The results of good compliance and permanence of treatment were those described in the table.nCompliancePermanenceAlendronate86363,27%64,77%Alendronate+colecalciferol2774,07%81,48%Ibandronate366,67%100%Risedronate2339,13%60,87%Raloxifene1100%100%Bazedoxifene10%0%Teriparatide9976,77% (*)73,74%Denosumab31076,77% (*)74,52% (*)(*) p<0.05 for total bisphosphonates and for alendronateConclusion:The results obtained suggest that a small number of patients were treated after a hip fracture (20.49%) in addition the instituted treatments are followed in a suboptimal way. It is necessary to investigate which factors may lead to the detection of potential non-compliant patients. It seems appropriate to consider drugs that facilitate compliance and permanence of treatment.Our results suggest that denosumab and teriparatide improve compliance compared with oral bisphosphonates.The introduction of specific plans and cross-sectional health structures between levels of care should lead to improve detection, treatment and compliance in patients with osteoporosis.Disclosure of Interests:SILVIA PAREDES Consultant of: Amgen, Lilly, Ferrer, Roche, Novartis; BMS, Maria Guinovart: None declared, Aida Basco: None declared, Carles Llop: None declared

Linear Rail Space Dynamic Scheduling Technology for Multi-Tasking Hybrid Assembly Sections

2012 ◽  
Vol 271-272 ◽  
pp. 650-656
Author(s):  
Zhi Bing Lu ◽  
Ai Min Wang ◽  
Cheng Tong Tang ◽  
Jing Sheng Li
Keyword(s):  
Production Scheduling ◽  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Real Data ◽  
Utilization Rate ◽  
Filter Method ◽  
Scheduling Problem ◽  
Rule Based ◽  
Comprehensive Utilization ◽  
Space Production

For the rapid response to production scheduling problem driven by high-density production tasks, a dynamic scheduling technology for the large precision strip products assembly with a mixture of task time nodes and line-rail space is proposed. A scheduling constrained model containing coverage, proximity, timeliness and resource is established. A linear rail space production scheduling technology using heuristic automatic scheduling and event-driven method is put forward. The time rule based on delivery and single completion assembly is formed, at the same time the space rule based on the adjacent rail and comprehensive utilization is researched. Supposing the privilege of single product assembling as the core, the scheduling parts filter method based on multiple constraints and former rules. For the space layout problem, a clingy forward and backward algorithms is proposed to judge the assemble position regarding the space comprehensive utilization rate. The classification of the various disturbances in the actual production is summarized. Three basic algorithms are proposed, including insertion, moving and re-scheduling algorithm, in order to solve the assembly dynamic scheduling problem driven by production disturbance events. Finally, take rocket as the example， the rocket assembly space production scheduling system is developed, combining with the proposed algorithm. The practicability of the system is validated using real data.

Abstract WP429: A Nurse Driven Acute Stroke Alert Process Improves Treatment Times and Treatment Rates

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Daniel D'Amour ◽  
Jayme Strauss ◽  
Amy K Starosciak
Keyword(s):  
Treatment Time ◽  
Treatment Decision ◽  
Treatment Rate ◽  
Treatment Decision Making ◽  
National Rate ◽  
Number Of Patients ◽  
Stroke Team ◽  
Comprehensive Stroke Center ◽  
Stroke Center ◽  
Positive Effect

Introduction: Treatment time has gained sufficient popularity because it is now well-known that “Time is Brain”. Treatment rates, however, lag behind in importance even though more lives can be saved by treating more often. Our TJC Comprehensive Stroke Center has a nurse-led stroke alert process that focuses on multiple, rapid, parallel steps to reduce DTN for IV alteplase. The Baptist Emergency Stroke Team (BEST) responders are highly-trained and skilled nurses that assess, coordinate, and initiate processes to ensure the best times. We identified that our treatment rate was lower than the national rate for certified CSCs, so the BEST responders used a stepwise process to develop their own interventions to improve rates. Methods: First, the BEST responders started tracking our monthly rate. Next, they set a rate goal, and then brainstormed how to influence treatment decision-making. The BEST team initiated a monthly PI meeting that focused on the importance of treating disability rather than an NIHSS score. Then the team scripted and rehearsed critical conversations to have providers that advocated specifically for treating disability. The team adopted the motto, “Treat Disability, Not Numbers”. Results Conclusions: Our CSC observed a small decrease in median DTN but double the treatment rate after the BEST responder intervention. In comparison, these statistics did not change at the national CSC level. The sICH rate was reduced from Period A to C, meaning that increased treatment rate did not lead to increased hemorrhagic rate. Nursing initiatives can have a substantial positive effect on increasing the number of patients treated with IV alteplase for acute ischemic stroke.

scholarly journals Deep Learning: A New Horizon for Personalized Treatment of Depression?

2018 ◽  
Vol 16 (1) ◽  
Author(s):  
David Benrimoh ◽  
Robert Fratila ◽  
Sonia Israel ◽  
Kelly Perlman
Keyword(s):  
Deep Learning ◽  
Decision Aid ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Personalized Care ◽  
Treatment Of Depression ◽  
Number Of Patients ◽  
Treatment Plans ◽  
Patient Responses ◽  
Deep Learning Model

Globally, depression affects 300 million people and is projected be the leading cause of disability by 2030. While different patients are known to benefit from different therapies, there is no principled way for clinicians to predict individual patient responses or side effect profiles. A form of machine learning based on artificial neural networks, deep learning, might be useful for generating a predictive model that could aid in clinical decision making. Such a model’s primary outcomes would be to help clinicians select the most effective treatment plans and mitigate adverse side effects, allowing doctors to provide greater personalized care to a larger number of patients. In this commentary, we discuss the need for personalization of depression treatment and how a deep learning model might be used to construct a clinical decision aid.

Non-parametric treatment time-lag effect estimation

2021 ◽  
pp. 096228022110326
Author(s):  
Kristine Gierz ◽  
Kayoung Park ◽  
Peihua Qiu
Keyword(s):  
Survival Data ◽  
Treatment Time ◽  
Time Lag ◽  
Simulated Data ◽  
Real Data ◽  
Point Problem ◽  
Change Point Problem ◽  
Lag Effect ◽  
Effect Estimation ◽  
Non Parametric

In general, the change point problem considers inference of a change in distribution for a set of time-ordered observations. This has applications in a large variety of fields, and can also apply to survival data. In survival analysis, most existing methods compare two treatment groups for the entirety of the study period. Some treatments may take a length of time to show effects in subjects. This has been called the time-lag effect in the literature, and in cases where time-lag effect is considerable, such methods may not be appropriate to detect significant differences between two groups. In this paper, we propose a novel non-parametric approach for estimating the point of treatment time-lag effect by using an empirical divergence measure. Theoretical properties of the estimator are studied. The results from the simulated data and the applications to real data examples support our proposed method.

A Heuristic Algorithm for Optimizing Business Matchmaking Scheduling

2012 ◽  
Vol 3 (4) ◽  
pp. 59-73 ◽  
Author(s):  
Yingping Huang ◽  
Xihui Zhang ◽  
Paulette S. Alexander
Keyword(s):  
Heuristic Algorithm ◽  
Small Businesses ◽  
Real Data ◽  
Government Agencies ◽  
Scheduling Problem ◽  
Maximum Cardinality ◽  
Simulation Experiments ◽  
Matching Problems ◽  
3 Dimensional ◽  
Planar Assignment Problem

Business matchmaking is a service dedicated to providing one-on-one appointments for small businesses (or sellers) to meet with government agencies and large corporations (or buyers) for contracting opportunities. Business matchmaking scheduling seeks to maximize the total number of appointments with the maximum objective that weighs the preferences of both buyers and sellers. In this paper, the authors transformed the business matchmaking scheduling problem into a 3-dimensional planar assignment problem and solved it heuristically using a series of bipartite maximum weighted maximum cardinality matching problems. Simulation experiments and real data showed that this algorithm outperforms human experts and prior algorithm in terms of number of appointments, the objective that weighs buyer and seller’s preferences, and the execution time.

SU-GG-T-115: Inclusion of MLC Leakage in Treatment Plans to Reduce Monitor Units and Treatment Time

2010 ◽  
Vol 37 (6Part17) ◽  
pp. 3210-3211
Author(s):  
D Tedeschi ◽  
H Alkhatib ◽  
J Stenbeck ◽  
I Sundararaman
Keyword(s):  
Treatment Time ◽  
Treatment Plans

scholarly journals Employment of Emergency Advanced Nurses of Turkey: A Discrete-Event Simulation Application

Processes ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 48 ◽  
Author(s):  
Abdulkadir Atalan ◽  
Cem Donmez
Keyword(s):  
Length Of Stay ◽  
Discrete Event Simulation ◽  
Emergency Services ◽  
Treatment Time ◽  
Waiting Times ◽  
Discrete Event ◽  
Weekly Basis ◽  
Event Simulation ◽  
Number Of Patients ◽  
Efficiency Rate

In the present study, problems in emergency services (ESs) were dealt with by analyzing the working system of ESs in Turkey. The purpose of this study was to reduce the waiting times spent in hospitals by employing advanced nurses (ANs) to treat patients who are not urgent, or who may be treated as outpatients in ESs. By applying discrete-event simulation on a 1/24 (daily) and 7/24 (weekly) basis, and by employing ANs, it was determined that the number of patients that were treated increased by 26.71% on a 1/24 basis, and by 15.13% on a 7/24 basis. The waiting time that was spent from the admission to the ES until the treatment time decreased by 38.67% on a 1/24 basis and 53.66% on a 24/7 basis. Similarly, the length of stay was reduced from 82.46 min to 53.97 min in the ES. Among the findings, it was observed that the efficiency rate of the resources was balanced by the employment of ANs, although it was not possible to obtain sufficient efficiency from the resources used in the ESs prior to the present study.

scholarly journals Reducing Referral-to-Treatment Waiting Times in Cancer Patients Using a Multidisciplinary Database

2007 ◽  
Vol 89 (2) ◽  
pp. 113-117 ◽  
Author(s):  
SAR Nouraei ◽  
J Philpott ◽  
SM Nouraei ◽  
DCK Maude ◽  
GS Sandhu ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Cancer Patients ◽  
Treatment Planning ◽  
Neck Cancer ◽  
Treatment Time ◽  
Waiting Times ◽  
Multidisciplinary Teams ◽  
Number Of Patients ◽  
Cancer Plan

INTRODUCTION Modern delivery of cancer care through patient-centred multidisciplinary teams (MDT) has improved survival. This approach, however, requires effective on-going co-ordination between multiple specialties and resources and can present formidable organisational challenges. The aim of this study was to improve the efficiency of the MDT process for head and neck cancer. PATIENTS AND METHODS A systems analysis of the MDT process was undertaken to identify bottlenecks delaying treatment planning. The MDT process was then audited. A revised process was developed and an Intranet-based data management solution was designed and implemented. The MDT process was re-evaluated to complete the audit cycle. RESULTS We designed and implemented a trust-wide menu-driven database with interfaces for registering and tracking patients, and automated worklists for pathology and radiology. We audited our MDT for 11 and 10 weeks before and following the introduction of the database, with 226 and 187 patients being discussed during each period. The database significantly improved cross-specialtity co-ordination, leading to a highly significant reduction in the number of patients whose treatment planning was delayed due to unavailability of adjunctive investigations (P < 0.001). This improved the overall efficiency of the MDT by 60%. CONCLUSIONS The NHS Cancer Plan aspires to reduce the referral-to-treatment time to 1 month. We have shown that a simple, trust-wide database reduces treatment planning delays in a sizeable proportion of head and neck cancer patients with minimal resource implications. This approach could easily be applied in other MDT meetings.

(Re)descriptions of medical professional work: exploring accounting as a performative device within an emergency unit health-care context

2020 ◽  
Vol 32 (2) ◽  
pp. 159-176 ◽  
Author(s):  
Cemil Eren Fırtın ◽  
Tom S. Karlsson
Keyword(s):  
Health Care ◽  
Health Care Quality ◽  
Treatment Time ◽  
Medical Professional ◽  
Care Quality ◽  
Medical Terminology ◽  
Professional Work ◽  
Content Type ◽  
Emergency Health Care ◽  
Number Of Patients

PurposeThis article addresses issues of calculation and economization in contemporary public organizations. In particular, it investigates how choices of organizing emergency health-care have been affected by accounting as a performative device. Special attention has been paid to how accounting brings about performative consequences in shaping the medical profession and its context.Design/methodology/approachThe article employs qualitative research methods and draws its analysis on empirical data from in-depth interviews at an emergency health-care unit in Sweden.FindingsIt is demonstrated how accounting, in the form of calculations of treatment time and number of patients, enables performative consequences for medical professional work. It is also demonstrated how the use of accounting engages (re)descriptions of practices and roles, creates accounts of patients, and helps to sustain such (re)descriptions. Accounting terms (such as efficiency and control) have been reframed into medical terminology (such as health-care quality and security), ensuring and retaining (re)described medical professional work in terms of practices and emerging roles.Originality/valueThis article contributes to (1) the literature on accounting practices within health-care contexts by demonstrating a case where the accounting ideas and practices of medical professionals are coexistent and interwoven and (2) the increasing body of literature focusing on accountingization by showing how emerging calculative technologies carry performative power over medical professional work through formative (re)descriptions.

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